Digital transformation in the financial services sector requires the industry players to accept and adapt to new approaches to data access and management.
There are two main outdated approaches:
1. IT working with enterprise data warehouse and data mart along with ETL tools
2. Business processing the data manually with Excel
To name a couple of the challenges: Inflexibility of the IT department with long time-to-market cycles and lack of transparency, accountability, and auditability.
The solution to these challenges is Logical Data Warehouse which helps to close the chasm between IT and business and thereby save time by around 75% and cut costs by up to 70%.
Long time to market
The process of getting the data is so technical and complicated that only a limited number of people can do it (usually the IT or BI development department). That means, every time the data consumer needs the data they have to reach out to the IT/BI development team who then starts to prepare the data. And this takes so long that until the data consumer receives the data it is already outdated and/or not needed anymore.
Uncleansed raw data
In the early days of data warehousing, many companies didn’t allow the cleansing of the raw data. That means if the quality of the data is bad the result that comes out is also bad or even wrong: garbage in, garbage out. In order to avoid that, everybody who uses the data cleans it in their own report respectively. Hence, there are several different versions of data truth out there.
Limited access to different data sources
Many financial institutions built their data warehouse systems when commercial data wasn’t as popular as they are now. The challenge is that the commercial data cannot be easily connected because this wasn’t initially considered when the system was built.
No or limited access to real-time data
Real-time data now plays an essential role in financial processes. For instance, a loan application comes in from somebody who’s at the car dealer and wants to buy a car. For this kind of situation, real-time data related to this loan requester is crucial.
HOW DATA VIRTUALITY ENABLES YOU TO OVERCOME THESE CHALLENGES
VOICES FROM OUR CUSTOMERS
DMO Manager, Crédit Agricole Consumer Finance
'Data Virtuality is so easy to use that even our business analysts can use it and get the data whenever they need it. Before Data Virtuality only our developers could use the tool and the business analysts had to wait. Now that the developers as well as business analysts can use the solution, we are not only more efficient but were able to cut cost by 70%!'
DATA VIRTUALITY BENEFITS
SAVE TIME AND CUT COST
EASE OF USE
BETTER DATA GOVERNANCE
ALWAYS GDPR COMPLIANT
COMBINE HISTORICAL AND REAL-TIME DATA
RELEVANT KEY FEATURES
A CENTRAL DATA MODEL
200+ READY-TO-USE CONNECTORS
BY ADDING THE VIRTUAL LAYER IN DATA VIRTUALITY, …
... you can ensure higher quality of data as you provide data from one single source of truth to all business users
... you can speed up time-to-market because of a highly agile platform.
... you can always be GDPR compliant as you don’t have to store the data anywhere thanks to the virtual layer and the real-time connection